code: def cluster_scope():
      """Provides a scope in which Clustered layers and models can be deserialized.
  
      If a keras model or layer has been clustered, it needs to be within this scope
      to be successfully deserialized.
  
      Returns:
          Object of type `CustomObjectScope` with clustering objects included.
  
      Example:
  
      ```python
      clustered_model = cluster_weights(model, **self.params)
      tf.keras.models.save_model(clustered_model, keras_file)
  
      with cluster_scope():
        loaded_model = tf.keras.models.load_model(keras_file)
      ```
      """
      return CustomObjectScope(
          {"ClusterWeights": cluster_wrapper.ClusterWeights}
      )
  
file_path: model-optimization/tensorflow_model_optimization/python/core/clustering/keras/cluster.py
imports: import warnings
  import tensorflow
  from tensorflow_model_optimization.python.core.clustering.keras import cluster_config
  from tensorflow_model_optimization.python.core.clustering.keras import cluster_wrapper
  from tensorflow_model_optimization.python.core.clustering.keras import clustering_centroids
label_desc: Use image node_id 1 for calling a global function with example usage: cluster_scope() and returns: CustomObjectScope